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基于ROS的移动机器人定位与地图构建
隋景峰
Subtype工程硕士
Thesis Advisor王硕
2017-05-25
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword移动机器人 外参数标定 多传感器信息融合 自主定位 地图构建
Abstract移动机器人自主定位是机器人在未知环境中作业的基础。近年来,基于多传感器信
息融合的机器人定位与导航受到越来越多的关注,被认为是提高机器人导航系统的准
确性和鲁棒性的有效途径。本文针对移动机器人感知系统的设计与标定、移动机器人自
主定位、环境地图构建等方面开展了研究工作。主要内容如下:
一、给出了一种移动机器人感知系统的设计方案,介绍了立体相机内参数、外参数的
标定原理和方法,提出了一种基于棋盘格标定板的双目相机与16 线激光雷达、
双目相机与单线激光测距传感器的外参数标定方法,并通过实验验证了所提标
定方法的准确性。
二、论文分别实现了基于差分编码器、姿态航向参考系统、立体视觉里程计的移动机
器人位姿估计方法,并在ROS 平台上利用扩展卡尔曼滤波器对所实现的三种位
姿估计方法进行了信息融合。该方法提高了移动机器人自主定位的精度和鲁棒
性,论文通过在多个场景下开展移动机器人的自主定位实验对所提方法的有效
性进行了验证。
三、论文将所实现的定位方法应用于ROS 平台提供的地图构建功能包中,实现了移
动机器人在未知环境中的地图构建功能。论文在多个场景下开展了地图构建实
验,构建出的地图都较为精准,验证了所提方法的有效性。
Other AbstractAutonomous mobile robot localization is the basis of the robot operation in unknown
environments. Multi-sensor based robot localization and navigation have attracted more
and more attention in the recent years, which is considered to be an effective way to
improve the accuracy and robustness of robot navigation. In this paper, we briefly
introduce the laser sensors and stereo camera based robot perception system, an accuracy
and robust extrinsic calibration method is developed for our sensor system. then, the
research on autonomous robot location and maping based on our calibrated sensor system
is conducted. The main contents are as follows:
1. The sensor system of our research platform was introduced. The principle and
methods of the intrinsic and extrinsic calibration of the stereo camera are given.
Chessboard based extrinsic calibration between a zed setero camera with Velodyne
LiDAR and the extrinsic between zed setero camera with sick lms111 laser
rangefinderbased is proposed. Experment results show the effectiveness of the
proposed method.
2. The pose estimation methods of mobile robot based on differential encode, attitude
heading reference system and stereo visual odometry are implemented respectively
in this paper. The extended kalman filter is implemented on ROS
platform to improve the accuracy and robustness of the robot location by fusing
the information from wheel odometry, AHRS and the stereo odometry. Multiple
sets of experiments are carried out in both indoor and outdoor environments.
Experment results show the effectiveness of the proposed method.
3. The implemented location method is provided to the ROS map building package,
which is used to build 2D grid map for mobile robot in unknown environments.
Experiments are carried out in several different environments, the generated maps
are accurate.
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14808
Collection毕业生_硕士学位论文
Affiliation中科院自动化研究所
Recommended Citation
GB/T 7714
隋景峰. 基于ROS的移动机器人定位与地图构建[D]. 北京. 中国科学院研究生院,2017.
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